Seuraa
Sylvestre-Alvise Rebuffi
Sylvestre-Alvise Rebuffi
Google DeepMind
Vahvistettu sähköpostiosoite verkkotunnuksessa deepmind.com
Nimike
Viittaukset
Viittaukset
Vuosi
iCaRL: Incremental Classifier and Representation Learning
SA Rebuffi, A Kolesnikov, G Sperl, CH Lampert
CVPR 2017, 2017
37302017
Learning multiple visual domains with residual adapters
SA Rebuffi, H Bilen, A Vedaldi
NeurIPS 2017, 2017
8732017
Efficient parametrization of multi-domain deep neural networks
SA Rebuffi, H Bilen, A Vedaldi
CVPR 2018, 2018
3992018
Fixing data augmentation to improve adversarial robustness
SA Rebuffi, S Gowal, DA Calian, F Stimberg, O Wiles, T Mann
arXiv preprint arXiv:2103.01946, 2021
2482021
Data Augmentation Can Improve Robustness
SA Rebuffi, S Gowal, DA Calian, F Stimberg, O Wiles, T Mann
NeurIPS 2021, 2021
2422021
Improving Robustness using Generated Data
S Gowal, SA Rebuffi, O Wiles, F Stimberg, DA Calian, T Mann
NeurIPS 2021, 2021
2312021
A fine-grained analysis on distribution shift
O Wiles, S Gowal, F Stimberg, SA Rebuffi, I Ktena, T Cemgil
ICLR 2022, 2021
1962021
Automatically discovering and learning new visual categories with ranking statistics
K Han, SA Rebuffi, S Ehrhardt, A Vedaldi, A Zisserman
ICLR 2020, 2020
1892020
Modeling of Store Gletscher's calving dynamics, West Greenland, in response to ocean thermal forcing
M Morlighem, J Bondzio, H Seroussi, E Rignot, E Larour, A Humbert, ...
Geophysical Research Letters 43 (6), 2659-2666, 2016
1422016
There and Back Again: Revisiting Backpropagation Saliency Methods
SA Rebuffi, R Fong, X Ji, A Vedaldi
CVPR 2020, 2020
1332020
Autonovel: Automatically discovering and learning novel visual categories
K Han, SA Rebuffi, S Ehrhardt, A Vedaldi, A Zisserman
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
1002021
Semi-supervised learning with scarce annotations
SA Rebuffi, S Ehrhardt, K Han, A Vedaldi, A Zisserman
Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020
522020
Defending against image corruptions through adversarial augmentations
DA Calian, F Stimberg, O Wiles, SA Rebuffi, A Gyorgy, T Mann, S Gowal
ICLR 2022, 2021
472021
Lsd-c: Linearly separable deep clusters
SA Rebuffi, S Ehrhardt, K Han, A Vedaldi, A Zisserman
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
272021
Generative models improve fairness of medical classifiers under distribution shifts
I Ktena, O Wiles, I Albuquerque, SA Rebuffi, R Tanno, AG Roy, S Azizi, ...
Nature Medicine, 1-8, 2024
152024
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts
F Croce, SA Rebuffi, E Shelhamer, S Gowal
CVPR 2023, 2023
122023
Nevis' 22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research
J Bornschein, A Galashov, R Hemsley, A Rannen-Triki, Y Chen, ...
Journal of Machine Learning Research 24 (308), 1-77, 2023
112023
Revisiting adapters with adversarial training
SA Rebuffi, F Croce, S Gowal
ICLR 2023, 2022
92022
A fine-grained analysis of robustness to distribution shifts
O Wiles, S Gowal, F Stimberg, SA Rebuffi, I Ktena, KD Dvijotham, ...
NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021
22021
Adversarially self-supervised pre-training improves accuracy and robustness
SA Rebuffi, O Wiles, E Shelhamer, S Gowal
12023
Järjestelmä ei voi suorittaa toimenpidettä nyt. Yritä myöhemmin uudelleen.
Artikkelit 1–20